Touch sensing systems (“touch systems”) are in widespread use in a variety of applications. Typically, the touch sensing systems are actuated by a touch object such as a finger or stylus, either in direct contact or through proximity (i.e. without contact) with a touch surface. Touch sensing systems are for example used as touch pads of laptop computers, in control panels, and as overlays to displays on e.g. hand held devices, such as mobile telephones. A touch panel that is overlaid on or integrated in a display is also denoted a “touch screen”. Many other applications are known in the art.
To an increasing extent, touch systems are designed to be able to detect two or more touches simultaneously, this capability often being referred to as “multi-touch” in the art.
There are numerous known techniques for providing multi-touch sensitivity, e.g. by using cameras to capture light scattered off the point(s) of touch on a touch panel, or by incorporating resistive wire grids, capacitive sensors, strain gauges, etc into a touch panel.
WO2010/064983 and WO2010/06882 disclose another type of multi-touch system which is based on frustrated total internal reflection (FTIR). Light sheets are coupled into a panel to propagate inside the panel by total internal reflection. When an object comes into contact with a touch surface of the panel, two or more light sheets will be locally attenuated at the point of touch. Arrays of light sensors are located around the perimeter of the panel to detect the received light for each light sheet. Data from the light sensors may be processed into logarithmic transmission values, which are input into an image reconstruction algorithm that generates a two-dimensional (2D) distribution of attenuation values over the touch surface. This enables determination of shape, position and size of multiple touches.
The prior art also comprises WO2011/049511 which proposes image reconstruction based on the use of a projection function that models the impact on the received light when a touching object interacts with the light that propagates on different paths (detection lines) across the touch surface. The projection function defines a functional relation between projected values for the detection lines and a 2D distribution of attenuation values across the touch surface. The 2D distribution is generated by finding an optimum of an optimization function that includes an aggregation of absolute differences between projected values, given by the projection function, and observed values for the different detection lines. The optimization function may be obtained by Bayesian inversion.
Irrespective of sensor technology, the touches need to be detected against a background of measurement noise and other interferences, e.g. originating from ambient light, fingerprints and other types of smear on the touch surface, vibrations, detection artifacts, etc. The influence of measurement noise and interferences may vary not only over time but also within the extent of the touch surface, making it difficult to properly detect the touches on the touch surface at all times. Furthermore, the degree of interaction between a touching object and the touch surface may vary both over time and between different objects. For example, the interaction may depend on if an object is tapped, dragged or held in a fixed position onto the touch surface. Different objects may yield different degree of interaction, e.g. the degree of interaction may vary between fingers of a user, and even more so between the fingers of different users.
The combination of several touches, complex gestures as well as temporal and spatial variations in degree of interaction, background, and noise will make the identification of touches a more demanding task. The user experience will be greatly hampered if, e.g., an ongoing gesture on a touch screen is interrupted by the system failing to detect certain touches during the gesture.